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R Data Mining

You're reading from R Data Mining

Product type Book

Published in Nov 2017

Publisher Packt

ISBN-13 9781787124462

Pages 442 pages

Edition 1st Edition

Languages

Concepts

Table of Contents (22) Chapters

Title Page

Credits

About the Author

About the Reviewers

www.PacktPub.com

Customer Feedback

Preface

1. Why to Choose R for Your Data Mining and Where to Start

2. A First Primer on Data Mining Analysing Your Bank Account Data

3. The Data Mining Process - CRISP-DM Methodology

4. Keeping the House Clean – The Data Mining Architecture

5. How to Address a Data Mining Problem – Data Cleaning and Validation

6. Looking into Your Data Eyes – Exploratory Data Analysis

7. Our First Guess – a Linear Regression

8. A Gentle Introduction to Model Performance Evaluation

9. Don't Give up – Power up Your Regression Including Multiple Variables

10. A Different Outlook to Problems with Classification Models

11. The Final Clash – Random Forests and Ensemble Learning

12. Looking for the Culprit – Text Data Mining with R

13. Sharing Your Stories with Your Stakeholders through R Markdown

14. Epilogue

15. Dealing with Dates, Relative Paths and Functions

Principles of a good data mining report

I have written quite a lot of reports, highlighting results from a wide range of activities. Based on the feedback received and from the requests of changes intervened from the first version to the definitive one, I can tell you the following basic principles for producing a good data mining report:

Clearly show the objectives and questions that initiated the analyses performed
Explicitly highlight the assumptions made when performing the analyses
Enumerate and get into the details with data treatment applied to analyzed data
Always verify that the reproduced data is consistent
Provide data lineage to the maximum possible extent

Let's get a bit deeper into these principles before we actually develop our report.

Clearly state the objectives

When I was a newbie in the field, I got really excited at the idea of applying all the data mining techniques I knew by then to real data. You can imagine my happiness when I was first provided with a bunch of data. I was...

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